Key Aspects of a Generative AI Strategy in Software Testing CT-GENAI Practice Questions (Page 5)

Questions 21–25

1. 21application · medium

   A multinational company is deploying a generative AI tool for test automation. The tool will be used by teams in different countries, and the company must comply with GDPR for data processed in the EU. What should the company include in its governance plan?

   • AA requirement that all AI-generated test data be stored in the EU.
   • BA plan to anonymize all personal data before using the AI tool.
   • CA policy that prohibits the use of generative AI for any testing involving personal data.
   • DA data processing agreement with the AI vendor that specifies GDPR compliance.
   Reveal Solution Discussion Select an answer first
2. 22expert · hard

   A company operates in a highly regulated industry and wants to use generative AI to create test data that includes personal data. The legal team requires that the AI model be transparent and explainable. The testing team wants to use a state-of-the-art large language model. What is the best approach to balance these requirements?

   • AUse the large language model and document that it is a black box, accepting the risk.
   • BAvoid using AI for test data generation and use only manual methods.
   • CUse the large language model but add a post-hoc explanation tool to generate justifications.
   • DUse a simpler, more interpretable AI model that can provide explanations for its outputs.
   Reveal Solution Discussion Select an answer first
4. 23application · medium

   A testing team has implemented a generative AI tool that automatically creates test cases from user stories. After three months, they want to evaluate whether the tool is effective. Which metric would best measure the effectiveness of the AI-generated test cases?

   • AThe number of test cases generated per user story.
   • BThe percentage of AI-generated test cases that detect defects.
   • CThe time saved in test creation compared to manual creation.
   • DThe number of user stories covered by AI-generated tests.
   Reveal Solution Discussion Select an answer first
5. 24application · medium

   A mid-sized financial services company wants to adopt generative AI for test case generation. The compliance team has flagged concerns about data privacy and the need to keep sensitive customer data within the organization. The testing team has limited experience with AI tools. What should the organization do first to assess readiness for this adoption?

   • AConduct a readiness assessment that evaluates current data governance, team AI skills, infrastructure, and compliance requirements before selecting tools.
   • BPurchase a commercial generative AI testing tool and pilot it on a non-sensitive internal project to build team experience.
   • CHire external AI consultants to build a custom in-house generative AI solution that keeps all data on-premises.
   • DImmediately implement a governance framework that restricts all generative AI use to synthetic data only, regardless of the use case.
   Reveal Solution Discussion Select an answer first
6. 25foundation · easy

   Which of the following is a potential risk of using generative AI in software testing?

   • AAI-generated test cases may contain biases that lead to incomplete coverage
   • BAI eliminates the need for test data privacy
   • CAI will always produce correct test results
   • DAI makes testing completely independent of human oversight
   Reveal Solution Discussion Select an answer first